In this research, a selection of some mineral water was selected on the basis of being the most marketed by the owners of shops in Najaf province, with six types, where daily samples of this water were taken by 50 ml for two months from (1/11/2018 -1/1/2019). The following ions concentrations were measured (Br-, Cl-, F-, NO3-, SO42-, Na+, K+, Ca2+, Mg2+), pH and the electrical conductivity were measured and the results were compared with the allowable rates according to the international organizations. It was noted that they conform to international and Iraqi standards.

In this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

Discotic liquid crystal compounds were synthesized and characterized. Liquid crystalline texture of these compounds was investigated by polarized optical microscopy (POM). The Hartree-Fock approximation (HF) was used to calculate theoretical molecular parameters for synthesized compounds such as optimization, hardness, EHOMO, ELUMO, and energy gap using the Gaussian 09W program.

The present study aimed to synthesize selenium nanoparticles (SeNPs) using aqueous extract of black currant as a reducing agent. The green synthesized black currant selenium nanoparticles (BCSeNPs) were identified by color change. The characterization of SeNPs was achieved by Ultraviolet-visible (UV–VIS) spectroscopy, scanning electron microscopy (SEM), X–ray diffraction analysis (XRD), and Fourier transform infrared spectroscopy (FTIR). These tests were used to detect: stability, morphology, size, crystalline nature, and functional groups present on the surface of BCSeNPs. The results revealed appearance of the brick-red color indicating the specific color of selenium nanoparticles, and UV-Vis spectroscopy showed band absorbanc